Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-08-04 11:14:57	ga_ls8c_ard_3-0-0_109078_2015-08-04_final
2015-08-04 11:15:20	ga_ls8c_ard_3-0-0_109079_2015-08-04_final
2016-02-26 11:23:59	ga_ls8c_ard_3-0-0_111069_2016-02-26_final
2016-02-26 11:24:23	ga_ls8c_ard_3-0-0_111070_2016-02-26_final
2016-02-26 11:24:47	ga_ls8c_ard_3-0-0_111071_2016-02-26_final
2016-02-26 11:25:11	ga_ls8c_ard_3-0-0_111072_2016-02-26_final
2016-02-26 11:25:35	ga_ls8c_ard_3-0-0_111073_2016-02-26_final
2016-02-26 11:25:59	ga_ls8c_ard_3-0-0_111074_2016-02-26_final
2016-02-28 11:15:13	ga_ls8c_ard_3-0-0_109078_2016-02-28_final
2016-02-28 11:15:37	ga_ls8c_ard_3-0-0_109079_2016-02-28_final
2016-02-28 11:16:01	ga_ls8c_ard_3-0-0_109080_2016-02-28_final
2016-02-28 11:16:25	ga_ls8c_ard_3-0-0_109081_2016-02-28_final
2016-02-28 11:16:49	ga_ls8c_ard_3-0-0_109082_2016-02-28_final
2016-02-28 11:17:13	ga_ls8c_ard_3-0-0_109083_2016-02-28_final
2016-03-15 11:15:09	ga_ls8c_ard_3-0-0_109078_2016-03-15_final
2016-03-15 11:15:33	ga_ls8c_ard_3-0-0_109079_2016-03-15_final
2016-03-15 11:15:57	ga_ls8c_ard_3-0-0_109080_2016-03-15_final
2016-03-15 11:16:21	ga_ls8c_ard_3-0-0_109081_2016-03-15_final
2016-03-15 11:16:45	ga_ls8c_ard_3-0-0_109082_2016-03-15_final
2016-03-15 11:17:09	ga_ls8c_ard_3-0-0_109083_2016-03-15_final
2016-04-21 11:29:01	ga_ls8c_ard_3-0-0_112067_2016-04-21_final
2016-04-21 11:29:25	ga_ls8c_ard_3-0-0_112068_2016-04-21_final
2016-04-21 11:29:49	ga_ls8c_ard_3-0-0_112069_2016-04-21_final
2016-04-23 11:19:02	ga_ls8c_ard_3-0-0_110073_2016-04-23_final
2016-04-23 11:19:25	ga_ls8c_ard_3-0-0_110074_2016-04-23_final
2016-04-23 11:19:49	ga_ls8c_ard_3-0-0_110075_2016-04-23_final
2016-04-23 11:20:13	ga_ls8c_ard_3-0-0_110076_2016-04-23_final
2016-04-23 11:20:37	ga_ls8c_ard_3-0-0_110077_2016-04-23_final
2016-04-23 11:21:01	ga_ls8c_ard_3-0-0_110078_2016-04-23_final
2016-04-23 11:21:25	ga_ls8c_ard_3-0-0_110079_2016-04-23_final
2019-06-26 11:23:58	ga_ls8c_ard_3-1-0_111069_2019-06-26_final
2019-06-26 11:24:22	ga_ls8c_ard_3-1-0_111070_2019-06-26_final
2019-06-26 11:24:46	ga_ls8c_ard_3-1-0_111071_2019-06-26_final
2019-06-26 11:25:10	ga_ls8c_ard_3-1-0_111072_2019-06-26_final
2019-06-26 11:25:34	ga_ls8c_ard_3-1-0_111073_2019-06-26_final
2019-06-26 11:25:58	ga_ls8c_ard_3-1-0_111074_2019-06-26_final
2019-06-28 11:15:13	ga_ls8c_ard_3-1-0_109078_2019-06-28_final
2019-06-28 11:15:37	ga_ls8c_ard_3-1-0_109079_2019-06-28_final
2019-06-28 11:16:01	ga_ls8c_ard_3-1-0_109080_2019-06-28_final
2019-06-28 11:16:24	ga_ls8c_ard_3-1-0_109081_2019-06-28_final
2019-06-28 11:16:48	ga_ls8c_ard_3-1-0_109082_2019-06-28_final
2019-06-28 11:17:12	ga_ls8c_ard_3-1-0_109083_2019-06-28_final
2019-07-12 11:24:02	ga_ls8c_ard_3-1-0_111069_2019-07-12_final
2019-07-12 11:24:26	ga_ls8c_ard_3-1-0_111070_2019-07-12_final
2019-07-12 11:24:50	ga_ls8c_ard_3-1-0_111071_2019-07-12_final
2019-07-12 11:25:13	ga_ls8c_ard_3-1-0_111072_2019-07-12_final
2019-07-12 11:25:37	ga_ls8c_ard_3-1-0_111073_2019-07-12_final
2019-07-12 11:26:01	ga_ls8c_ard_3-1-0_111074_2019-07-12_final
2019-07-14 11:15:16	ga_ls8c_ard_3-1-0_109078_2019-07-14_final
2019-07-14 11:15:40	ga_ls8c_ard_3-1-0_109079_2019-07-14_final
2019-07-14 11:16:04	ga_ls8c_ard_3-1-0_109080_2019-07-14_final
2019-07-14 11:16:28	ga_ls8c_ard_3-1-0_109081_2019-07-14_final
2019-07-14 11:16:52	ga_ls8c_ard_3-1-0_109082_2019-07-14_final
2019-07-14 11:17:15	ga_ls8c_ard_3-1-0_109083_2019-07-14_final
2019-07-28 11:24:07	ga_ls8c_ard_3-1-0_111069_2019-07-28_final
2019-07-28 11:24:31	ga_ls8c_ard_3-1-0_111070_2019-07-28_final
2019-07-28 11:24:55	ga_ls8c_ard_3-1-0_111071_2019-07-28_final
2019-07-28 11:25:19	ga_ls8c_ard_3-1-0_111072_2019-07-28_final
2019-07-28 11:25:43	ga_ls8c_ard_3-1-0_111073_2019-07-28_final
2019-07-28 11:26:07	ga_ls8c_ard_3-1-0_111074_2019-07-28_final
2019-07-30 11:15:21	ga_ls8c_ard_3-1-0_109078_2019-07-30_final
2019-07-30 11:15:45	ga_ls8c_ard_3-1-0_109079_2019-07-30_final
2019-07-30 11:16:09	ga_ls8c_ard_3-1-0_109080_2019-07-30_final
2019-07-30 11:16:33	ga_ls8c_ard_3-1-0_109081_2019-07-30_final
2019-07-30 11:16:57	ga_ls8c_ard_3-1-0_109082_2019-07-30_final
2019-07-30 11:17:21	ga_ls8c_ard_3-1-0_109083_2019-07-30_final
2019-08-13 11:24:13	ga_ls8c_ard_3-1-0_111069_2019-08-13_final
2019-08-13 11:24:37	ga_ls8c_ard_3-1-0_111070_2019-08-13_final
2019-08-13 11:25:01	ga_ls8c_ard_3-1-0_111071_2019-08-13_final
2019-08-13 11:25:25	ga_ls8c_ard_3-1-0_111072_2019-08-13_final
2019-08-13 11:25:49	ga_ls8c_ard_3-1-0_111073_2019-08-13_final
2019-08-13 11:26:13	ga_ls8c_ard_3-1-0_111074_2019-08-13_final
2019-08-15 11:15:27	ga_ls8c_ard_3-1-0_109078_2019-08-15_final
2019-08-15 11:15:51	ga_ls8c_ard_3-1-0_109079_2019-08-15_final
2019-08-15 11:16:15	ga_ls8c_ard_3-1-0_109080_2019-08-15_final
2019-08-15 11:16:39	ga_ls8c_ard_3-1-0_109081_2019-08-15_final
2019-08-15 11:17:03	ga_ls8c_ard_3-1-0_109082_2019-08-15_final
2019-08-15 11:17:27	ga_ls8c_ard_3-1-0_109083_2019-08-15_final
2019-09-30 11:24:26	ga_ls8c_ard_3-1-0_111069_2019-09-30_final
2019-09-30 11:24:50	ga_ls8c_ard_3-1-0_111070_2019-09-30_final
2019-09-30 11:25:14	ga_ls8c_ard_3-1-0_111071_2019-09-30_final
2019-09-30 11:25:38	ga_ls8c_ard_3-1-0_111072_2019-09-30_final
2019-09-30 11:26:02	ga_ls8c_ard_3-1-0_111073_2019-09-30_final
2019-09-30 11:26:26	ga_ls8c_ard_3-1-0_111074_2019-09-30_final
2019-10-02 11:15:41	ga_ls8c_ard_3-1-0_109078_2019-10-02_final
2019-10-02 11:16:05	ga_ls8c_ard_3-1-0_109079_2019-10-02_final
2019-10-02 11:16:29	ga_ls8c_ard_3-1-0_109080_2019-10-02_final
2019-10-02 11:16:53	ga_ls8c_ard_3-1-0_109081_2019-10-02_final
2019-10-02 11:17:16	ga_ls8c_ard_3-1-0_109082_2019-10-02_final
2019-10-02 11:17:40	ga_ls8c_ard_3-1-0_109083_2019-10-02_final
2019-10-09 11:19:53	ga_ls8c_ard_3-1-0_110073_2019-10-09_final
2019-10-09 11:20:17	ga_ls8c_ard_3-1-0_110074_2019-10-09_final
2019-10-09 11:20:41	ga_ls8c_ard_3-1-0_110075_2019-10-09_final
2019-10-09 11:21:05	ga_ls8c_ard_3-1-0_110076_2019-10-09_final
2019-10-09 11:21:29	ga_ls8c_ard_3-1-0_110077_2019-10-09_final
2019-10-09 11:21:53	ga_ls8c_ard_3-1-0_110078_2019-10-09_final
2019-10-09 11:22:17	ga_ls8c_ard_3-1-0_110079_2019-10-09_final
2019-10-11 11:11:07	ga_ls8c_ard_3-1-0_108082_2019-10-11_final
2019-10-11 11:11:31	ga_ls8c_ard_3-1-0_108083_2019-10-11_final
2019-10-11 11:11:55	ga_ls8c_ard_3-1-0_108084_2019-10-11_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years